Soft computing has arisen as a standard presuming perspective; fuzzy ideas have advanced as imperative in the field of processing. The present chapter would expect to motivate and support the reader by giving all the necessary flavors empowering him to seek after and exude creative thoughts in the field of the fuzzy framework. The chapter presents the fundamental fuzzy ideas, including the operations performed on uncertainty sets. Fuzzy ideas and operations are contrasted with crispy sets for the better cognizance of the pursuers, specifically the naive. How the probabilistic and fuzzy frameworks (level of truthness) vary would be underscored with sufficient situations. Uncertainty, vagueness in the data, and historical crispy data when utilized later, would connect some vulnerability with it; an embodiment of such vulnerability and its need to consider in the processing is managed in detail. Different fuzzy membership functions commonly used are explored here. The underlying terminology (core, support and boundary) and its significance in the membership functions are explored. In the last segment of the section, text categorization (TC) application utilizing the fuzzy ideas in processing is investigated. The features in TC are transformed into fuzzy collections (soft, hard and blended) as feature reduction. Gaussian function is employed in the process of obtaining the fuzzy collections. Itemized steps during the time spent treating word-based data classification are talked about.